How to do face recognition and face detection in C++?

How to perform face recognition and face detection in C?

Introduction:
Face recognition and face detection are important research directions in the field of computer vision. They are widely used in image processing, security monitoring and other fields. This article will introduce how to use C language for face recognition and face detection, and give corresponding code examples.

1. Face Detection
Face detection refers to the process of locating and identifying faces in a given image. OpenCV is a popular computer vision library that provides functions related to face detection. The following is a simple sample code for face detection:

#include <opencv2/opencv.hpp>
#include <opencv2/objdetect.hpp>

int main()
{
    cv::CascadeClassifier faceDetector;
    faceDetector.load("haarcascade_frontalface_default.xml"); // 加载人脸检测器模型

    cv::Mat image = cv::imread("image.jpg");

    std::vector<cv::Rect> faces;
    faceDetector.detectMultiScale(image, faces, 1.1, 3, 0, cv::Size(50, 50));

    for (const auto& face : faces)
    {
        cv::rectangle(image, face, cv::Scalar(0, 0, 255), 2);
    }

    cv::imshow("Face Detection", image);
    cv::waitKey(0);

    return 0;
}

In the above code, we first load a trained face detector model "haarcascade_frontalface_default.xml". Then we read the image to be detected and use the detectMultiScale function to detect the face in the image. The detection result is saved in the faces variable in the form of a rectangular frame. Finally, we draw the detection results on the image and display them.

2. Face recognition
Face recognition refers to identifying the identity of the face in a given image based on a known face image library. OpenCV also provides related functions for face recognition. The following is a simple sample code for face recognition:

#include <opencv2/opencv.hpp>
#include <opencv2/face.hpp>

int main()
{
    cv::Ptr<cv::face::LBPHFaceRecognizer> faceRecognizer = cv::face::createLBPHFaceRecognizer();

    std::vector<cv::Mat> images;
    std::vector<int> labels;

    images.push_back(cv::imread("image1.jpg", cv::IMREAD_GRAYSCALE));
    labels.push_back(0); // 第一张图像的标签为0
    images.push_back(cv::imread("image2.jpg", cv::IMREAD_GRAYSCALE));
    labels.push_back(1); // 第二张图像的标签为1

    faceRecognizer->train(images, labels); // 训练人脸识别器

    cv::Mat testImage = cv::imread("test.jpg", cv::IMREAD_GRAYSCALE);
    int predictedLabel = faceRecognizer->predict(testImage); // 对测试图像进行识别

    cv::imshow("Test Image", testImage);
    cv::waitKey(0);

    return 0;
}

In the above code, we first created a LBPH (Local Binary Patterns Histograms) face recognizer. We then built a library of face images, with each image having a corresponding label. Next, we train the face recognizer using the train function. Finally, we read a test image to be recognized and use the predict function to recognize it and return the predicted label value.

Conclusion:
This article introduces how to use C language for face recognition and face detection, and gives corresponding code examples. Face recognition and face detection are important research directions in the field of computer vision, and they have broad application prospects in practical applications. By mastering relevant technologies and methods, we can implement efficient and accurate face recognition and face detection systems in C.

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